Email: ietcourses@theiet.org
ALL CAREER STAGES | UK-SPEC: A,B,E | TWO DAYS | LIVE VIRTUAL | CPD: 14 HOURS | COST: FROM £495
Predictive maintenance for critical industries technical training course
Smarter systems, better outcomes: the predictive maintenance advantage
We can run additional courses dependent on demand. Please contact us if you are interested in different dates.
About the technical training course
In today’s high-stakes industrial landscape, downtime isn’t just costly - it’s critical. Predictive maintenance is revolutionising how organisations manage assets, anticipate failures, and optimise performance.
This two-day live virtual course, Predictive Maintenance for Critical Industries, is designed to equip professionals with the knowledge and tools to harness data-driven insights and machine learning for smarter maintenance strategies.
Led by experts from Loweconex and guest industry specialists, the programme blends foundational theory with real-world applications. From understanding the principles of predictive maintenance and exploring cutting-edge sensor technologies, to tackling implementation challenges and diving into digital twin ecosystems, participants will gain a comprehensive view of how predictive maintenance is transforming sectors like energy, transport, and defence.
Key learning objectives
- Understand predictive maintenance fundamentals
- Define predictive maintenance, its origins, and how it differs from traditional strategies.
- Apply machine learning in predictive maintenance
- Grasp core ML concepts, identify common algorithms, and understand how models learn from condition data.
- Recognise and address implementation challenges
- Identify barriers such as data quality and integration issues and explore practical mitigation strategies.
- Explore digital twin technology
- Define digital twins, explain their components, and understand their role in predictive maintenance.
- Integrate theory with practical insights
- Combine foundational knowledge with real-world applications to design effective predictive maintenance strategies.
Who should attend?
- Asset Manager
- Operations Manager
- Reliability Manager
- Plant Manager
- Energy/Utility Systems Director
- SCADA Engineer/Technician
- Predictive Maintenance Engineer
- Facilities Manager
- Condition Monitoring Specialist
- Instrumentation and Control Technician
- Industrial/Process Engineer
- Automation Engineer
- Quality Assurance Manager
- Logistics and Support Manager
- Systems Maintenance Engineer
Andrew Williams
Andrew Williams
Data & Analytics Director, Loweconex
Andrew has a background in building services engineering and data science. He specialises in driving the creation of cutting-edge, data-driven solutions with expertise in AI/ML, IoT & remote monitoring. He is also the Vice Chair of the IET AI Technical Network committee.
Day one - Tuesday 7 July 2026
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08:55 |
Teams opens |
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09:00 |
Welcome day one and Introduction to the course |
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09:15 |
Session 1: Foundations of Predictive Maintenance This session introduces the core principles of predictive maintenance, including how it differs from preventive and reactive strategies, and its role in modern asset management. Trainer: Andrew Williams, Data & Analytics Director, Loweconex |
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10:15 |
Break |
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Session 2: Machine Learning approach for Predictive Maintenance This session explains how machine learning models (e.g., regression, classification, Trainer: Andrew Williams, Data & Analytics Director, Loweconex |
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12:00 |
Lunch |
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13:00
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Session 3: The Challenges of predictive maintenance This session will explore key obstacles such as data quality and availability, integration with legacy systems, model accuracy and reliability, cost of implementation, and the need for skilled personnel to interpret predictive insights and maintain AI/ML systems. Trainer: Andrew Williams, Data & Analytics Director, Loweconex |
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14:00 |
Break |
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14:15 |
Session 4: Data Acquisition, Sensor Technologies and Condition Monitoring This session focuses on the technologies that enable predictive maintenance. It covers sensor types, data acquisition methods, and condition monitoring techniques, with practical insights into how organisations can connect assets and begin their predictive journey. Trainer: David Tingle, Director of Operations, Lowconex |
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15:15 |
Break |
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Session 5: Critical Industries Case Study Led by a guest expert, this session explores how predictive maintenance is being successfully applied in sectors such as energy, transport, and defence, using a real-world case study to highlight practical outcomes, implementation challenges, and lessons learned. Trainer: to be confirmed |
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16:30 |
End of day one |
Day two - Wednesday 8 July 2026
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08:55 |
Teams opens |
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09:00 |
Welcome day two |
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Session 6: Digital twins part 1 This session introduces the concept of digital twins, explaining their role in simulating, monitoring, and optimising physical systems. It covers the theoretical underpinnings, including modelling approaches, data integration, and the relationship between digital twins and predictive analytics. Trainer: Andrew Williams, Data & Analytics Director, Loweconex |
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Session 7: Digital twins part 2 Led by a guest expert, this session showcases real-world applications of digital twins across industries. Through case studies, participants will see how digital twins are used to improve asset performance, support decision-making, and enable predictive maintenance at scale. Trainer: to be confirmed |
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11:00 |
Break |
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11:15 1 hour |
Session 8: Implementation challenges part 1 Focuses on the practical aspects of deploying predictive maintenance, including change management, cost-benefit analysis, and overcoming cultural and technical barriers. Trainer: David Tingle, Director of Operations, Lowconex |
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12:15 |
Lunch |
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13:15 1 hour |
Session 9: Implementation challenges part 2 A guest speaker will delve into the legal, ethical and security dimensions of predictive maintenance and digital twins, including data privacy, compliance, and cybersecurity risks. Trainer: to be confirmed |
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14:15 |
Break |
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14:30 |
Session 10: Interactive workshop and presentation (Example) Participants will work in groups to design a predictive maintenance strategy for a hypothetical organisation. This hands-on session reinforces learning and encourages practical application of concepts covered in the course. Trainer: to be confirmed |
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Q&A / panel discussion An open forum where participants can ask questions, share reflections, and engage with all speakers. This session encourages cross-disciplinary dialogue and deeper exploration of the day’s topics. |
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16:30 |
End of day two |
Please note that the programme is subject to change.
Course registration and pricing
Early-bird
(until 22 May 2026)
Member - £895
Non-member - £995
Student - £495
Standard tickets
(from 23 May 2026)
Member - £995
Non-member - £1095
Student - £495
Group booking discounts
10% discount for 3 to 5 delegates – PREDGR3TO5
15% discount for 6 plus delegates – PREDGR6PLUS
What's included in registration?
- Two days of interactive training delivered by five experts
- Access to trainer presentations
- 14 CPD hours and a certificate
Overseas participants
If you are attending the course from outside of the UK and are paying for your booking using a company payment card where the company is VAT Registered and is the registered card billing address, please use the registration link for a VAT registered overseas company.
This form will capture your Company VAT Registration number and will be subject to Out of Scope VAT. Otherwise, VAT is charged at the UK rate of 20%.
If you are from outside the UK but paying with a personal payment card, please use the overseas individual link.
Terms and conditions
All prices are per person. If you require a proforma invoice before booking and/or wish to pay via purchase order, please contact us: events@theiet.org. We regret that we cannot accept AMEX for online payments.
*All students must provide a copy of their student pass or letter of enrolment from their college or University.
Once registered please email your documentation to events@theiet.org along with your booking confirmation number.
Discount codes are for member and non-member delegate registration only, and not applicable to student bookings.
If you need to pay for your group by proforma invoice, please contact events@theiet.org.
Contact us